> ## Documentation Index > Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt > Use this file to discover all available pages before exploring further. # Monitor usage and cost > Monitor Pinecone Assistant usage and cost, set monthly spend alerts, and track token usage across chat, context retrieval, and evaluation. You can set up email alerts that track your organization's monthly spending. An alert notifies the recipients you choose when spending reaches a threshold you set, and it resets at the start of each monthly billing cycle. > [!NOTE] > > Spend alerts are available on the [Standard and Enterprise plans](https://www.pinecone.io/pricing/). They're not needed on the Starter or Builder plans, where usage is capped by plan quotas rather than billed per unit. ## Set a spend alert 1. Go to [Settings > Spend alerts](https://app.pinecone.io/organizations/-/settings/spend-alerts) in the Pinecone console. 2. Click **+ Add Alert**. 3. Enter the dollar amount for the spend alert. 4. Enter the email addresses to send the alert to. [Organization owners](https://docs.pinecone.io/admin/organizations/organizations-overview.md#organization-roles) are listed by default. 5. Click **Create**. ## Edit a spend alert 1. In the row of the spend alert you want to edit, click **ellipsis (...) menu > Edit**. 2. Change the dollar amount, the email addresses, or both. 3. Click **Update**. ## Auto-spend spike alert To protect against unexpected cost increases, Pinecone sends an alert when spending exceeds double your previous month's invoice. You can't change that threshold or delete the alert, but you can change which email addresses receive it and turn its notifications on or off. ## Monitor organization-level usage > [!NOTE] > > You must be an [organization owner or billing admin](https://docs.pinecone.io/admin/organizations/organizations-overview.md#organization-roles) to view usage across your Pinecone organization. Also, this feature is available only to organizations on the Standard or Enterprise plans. The **Usage** dashboard in the Pinecone console reports usage and costs across your organization. You can read the report there, download it as a CSV file, or export it with the Admin API (Enterprise plans only). For the steps, see [Download a usage report](https://docs.pinecone.io/admin/billing/download-usage-report.md). ## Monitor token usage Requests to the [chat](https://docs.pinecone.io/reference/api/latest/assistant/chat_assistant.md), [context retrieval](https://docs.pinecone.io/reference/api/latest/assistant/context_assistant.md), and [evaluation](https://docs.pinecone.io/reference/api/latest/assistant/metrics_alignment.md) API endpoints return a `usage` parameter with `prompt_tokens`, `completion_tokens`, and `total_tokens` generated. > [tab] Chat > > For [chat](https://docs.pinecone.io/guides/assistant/chat-standard-interface.md), tokens are defined as follows: > > * `prompt_tokens` are based on the messages sent to the assistant and the context snippets retrieved from the assistant and sent to a model. Messages sent to the assistant can include messages from the [chat history](https://docs.pinecone.io/guides/assistant/chat-standard-interface.md#provide-conversation-history) in addition to the newest message. > > `prompt_tokens` appear as **Assistants Input Tokens** on invoices. > * `completion_tokens` are based on the answer from the model. > > `completion_tokens` appear as **Assistants Output Tokens** on invoices. > * `total_tokens` is the sum of `prompt_tokens` and `completion_tokens`. > > ```json Example chat response {9-13} theme={null} > { > "finish_reason": "stop", > "message": { > "role": "assistant", > "content": "The Chief Financial Officer (CFO) of Netflix is Spencer Neumann." > }, > "id": "000000000000000030513193ccc52814", > "model": "gpt-4o-2024-11-20", > "usage": { > "prompt_tokens": 23626, > "completion_tokens": 21, > "total_tokens": 23647 > }, > "citations": [ > { > "position": 63, > "references": [ > { > "file": { > "status": "Available", > "id": "99305805-3844-41b5-af56-ee693ab80527", > "name": "Netflix-10-K-01262024.pdf", > "size": 1073470, > "metadata": null, > "updated_on": "2025-07-29T20:07:53.171752661Z", > "created_on": "2025-07-29T20:07:36.361322699Z", > "signed_url": "https://storage.googleapis.com/..." > }, > "pages": [ > 78, > 79, > 80 > ], > "highlight": null > }, > { > "file": { > "status": "Available", > "id": "99305805-3844-41b5-af56-ee693ab80527", > "name": "Netflix-10-K-01262024.pdf", > "size": 1073470, > "metadata": null, > "updated_on": "2025-07-29T20:07:53.171752661Z", > "created_on": "2025-07-29T20:07:36.361322699Z", > "signed_url": "https://storage.googleapis.com/..." > }, > "pages": [ > 77, > 78 > ], > "highlight": null > } > ] > } > ] > } > ``` > [tab] Context retrieval > > For [context retrieval](https://docs.pinecone.io/guides/assistant/context-snippets-overview.md), tokens are defined as follows: > > * `prompt_tokens` are based on the messages sent to the assistant and the context snippets retrieved from the assistant. Messages sent to the assistant can include messages from the chat history in addition to the newest message. > > `prompt_tokens` appear as **Assistants Context Tokens Processed** on invoices. > > * `completion_tokens` don't apply for context retrieval because, unlike for chat, there is no answer from a model. `completion_tokens` will always be 0. > > * `total_tokens` is the sum of `prompt_tokens` and `completion_tokens`. > > ```json Example context response {28-32} theme={null} > { > "snippets": [ > { > "type": "text", > "content": "edures, or caused such disclosure controls and procedures to be designed under our supervision, to\r\nensure that material information relating to the registrant, including its consolidated subsidiaries, ...", > "score": 0.86632514, > "reference": { > "type": "pdf", > "file": { > "status": "Available", > "id": "99305805-3844-41b5-af56-ee693ab80527", > "name": "Netflix-10-K-01262024.pdf", > "size": 1073470, > "metadata": null, > "updated_on": "2025-07-29T20:07:53.171752661Z", > "created_on": "2025-07-29T20:07:36.361322699Z", > "signed_url": "https://storage.googleapis.com/..." > }, > "pages": [ > 78, > 79, > 80 > ] > } > }, > ... > ], > "usage": { > "prompt_tokens": 22914, > "completion_tokens": 0, > "total_tokens": 22914 > }, > "id": "00000000000000007b6ad859184a31b3" > } > ``` > [tab] Response evaluation > > For [response evaluation](https://docs.pinecone.io/guides/assistant/evaluation-overview.md), tokens are defined as follows: > > * `prompt_tokens` are based on two requests to a model: The first request contains a question, answer, and ground truth answer, and the second request contains the same details plus generated facts returned by the model for the first request. > > `prompt_tokens` appear as **Assistants Evaluation Tokens Processed** on invoices. > * `completion_tokens` are based on two responses from a model: The first response contains generated facts, and the second response contains evaluation metrics. > > `completion_tokens` appear as **Assistants Evaluation Tokens Out** on invoices. > * `total_tokens` is the sum of `prompt_tokens` and `completion_tokens`. > > ```json Response evaluation response {17-21} theme={null} > { > "metrics": { > "correctness": 123, > "completeness": 123, > "alignment": 123 > }, > "reasoning": { > "evaluated_facts": [ > { > "fact": { > "content": "" > }, > "entailment": "entailed" > } > ] > }, > "usage": { > "prompt_tokens": 123, > "completion_tokens": 123, > "total_tokens": 123 > } > } > ```